{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f5cc7641d0>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(np.random.randn(50).cumsum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
